Abstract
Durability and remaining useful life (RUL) prediction techniques are ones of the key issues for proton exchange membrane fuel cell (FC) commercialization. Herein, the performance degradation of an FC is analyzed based on the whole lifetime experimental data (up to 6500 h). The voltage model with different patterns is developed based on the voltage data, which can be easily measured. The mechanism model is developed based on the evolution of degradation indices reflecting the degradation state. However, the former is sensitive to the local and periodic changes in the voltage curve, leading to a large prediction error, and the latter requires aging data from complex and high-cost characterization, limiting the practical applications. Therefore, a hybrid prediction model combining the voltage and mechanism model is proposed where the respective weight of each model is dynamically determined based on their local prediction errors. The results reveal that the maximum errors in RUL prediction are 9.72%, 3.90% and 2.01% for the voltage, mechanism and hybrid model, respectively, and the RUL prediction results of the hybrid model are close to actual RUL when those of the voltage model are far from the accuracy zone, indicating that the hybrid model provides credible RUL predictions with the highest accuracy.